class: center, middle, inverse, title-slide # Welcome to EAES 494! ## <br><br> Data Science & Statistics ### Gavin McNicol ### 2021-08-23 --- class: middle # Dr. Gavin McNicol McNicol Lab @ UIC <img src="data:image/png;base64,#img/gavin-headshot.jpeg" width="30%" style="display: block; margin: auto auto auto 0;" /> --- ## Data science .pull-left-wide[ - Data science is an exciting discipline that allows you to turn raw data into understanding, insight, and knowledge. - We're going to learn to do this in a `tidy` way -- more on that later! - This is a course on introduction to data science, with an emphasis on statistical thinking. ] --- ## Course FAQ .pull-left-wide[ **Q - What data science background does this course assume?** A - None. **Q - Is this an intro stat course?** A - While statistics `\(\ne\)` data science, they are very closely related and have tremendous of overlap. Hence, this course is a great way to get started with statistics. However this course is *not* your typical college statistics course. **Q - Will we be doing computing?** A - Yes. **Q - Will we be working with EaESy Data?** A - *Yes!* ] --- ## Course FAQ .pull-left-wide[ **Q - Is this an intro CS course?** A - No, but many themes are shared. **Q - What computing language will we learn?** A - R. **Q: Why not language X?** A: We can discuss that over ☕. ] --- class: middle # Software --- <img src="data:image/png;base64,#img/npctr.png" width="75%" style="display: block; margin: auto auto auto 0;" /> --- <img src="data:image/png;base64,#img/pedons.png" width="75%" style="display: block; margin: auto auto auto 0;" /> --- <img src="data:image/png;base64,#img/excel.png" width="75%" style="display: block; margin: auto auto auto 0;" /> --- <img src="data:image/png;base64,#img/r.png" width="50%" style="display: block; margin: auto auto auto 0;" /> --- <img src="data:image/png;base64,#img/rstudio.png" width="73%" style="display: block; margin: auto auto auto 0;" /> --- class: middle # Data science life cycle --- <img src="data:image/png;base64,#img/data-science-cycle/data-science-cycle.001.png" width="90%" style="display: block; margin: auto auto auto 0;" /> --- <img src="data:image/png;base64,#img/data-science-cycle/data-science-cycle.002.png" width="90%" style="display: block; margin: auto auto auto 0;" /> --- <img src="data:image/png;base64,#img/data-science-cycle/data-science-cycle.003.png" width="90%" style="display: block; margin: auto auto auto 0;" /> --- <img src="data:image/png;base64,#img/data-science-cycle/data-science-cycle.004.png" width="90%" style="display: block; margin: auto auto auto 0;" /> --- <img src="data:image/png;base64,#img/data-science-cycle/data-science-cycle.005.png" width="90%" style="display: block; margin: auto auto auto 0;" /> --- <img src="data:image/png;base64,#img/data-science-cycle/data-science-cycle.006.png" width="90%" style="display: block; margin: auto auto auto 0;" /> --- .pull-left[ <img src="data:image/png;base64,#img/google-trend-index.png" width="100%" style="display: block; margin: auto auto auto 0;" /> ] .pull-right[ <img src="data:image/png;base64,#img/data-science-cycle/data-science-cycle.006.png" width="90%" style="display: block; margin: auto 0 auto auto;" /> ] --- .pull-left[ <img src="data:image/png;base64,#img/google-trend-index.png" width="75%" style="display: block; margin: auto auto auto 0;" /> ] .pull-right[ <img src="data:image/png;base64,#img/data-science-cycle/data-science-cycle.006.png" width="90%" style="display: block; margin: auto 0 auto auto;" /> ``` ## # A tibble: 5 x 2 ## date season ## <chr> <chr> ## 1 23 January 2017 winter ## 2 4 March 2017 spring ## 3 14 June 2017 summer ## 4 1 September 2017 fall ## 5 ... ... ``` ] --- <img src="data:image/png;base64,#img/data-science-cycle/data-science-cycle.007.png" width="90%" style="display: block; margin: auto auto auto 0;" /> --- <img src="data:image/png;base64,#img/data-science-cycle/data-science-cycle.008.png" width="90%" style="display: block; margin: auto auto auto 0;" /> --- <img src="data:image/png;base64,#img/data-science-cycle/data-science-cycle.009.png" width="90%" style="display: block; margin: auto auto auto 0;" /> --- <img src="data:image/png;base64,#img/carbon-emissions/carbon-emissions.png" width="85%" style="display: block; margin: auto auto auto 0;" /> --- class: middle # Let's dive in! --- <img src="data:image/png;base64,#img/carbon-emissions/carbon-emissions-01.png" width="100%" style="display: block; margin: auto;" /> --- class: inverse <img src="data:image/png;base64,#img/carbon-emissions/carbon-emissions-02.png" width="80%" /> --- class: inverse <img src="data:image/png;base64,#img/carbon-emissions/carbon-emissions-03.png" width="80%" /> --- class: inverse <img src="data:image/png;base64,#img/carbon-emissions/carbon-emissions-04.png" width="80%" /> --- class: inverse <img src="data:image/png;base64,#img/carbon-emissions/carbon-emissions-05.png" width="80%" /> --- class: inverse <img src="data:image/png;base64,#img/carbon-emissions/carbon-emissions-06.png" width="60%" /> --- class: inverse <img src="data:image/png;base64,#img/carbon-emissions/carbon-emissions-07.png" width="60%" /> --- class: inverse <img src="data:image/png;base64,#img/carbon-emissions/carbon-emissions-08.png" width="60%" /> --- class: inverse <img src="data:image/png;base64,#img/carbon-emissions/carbon-emissions-09.png" width="60%" /> --- class: inverse <img src="data:image/png;base64,#img/carbon-emissions/carbon-emissions-10.png" width="60%" /> --- class: inverse <img src="data:image/png;base64,#img/carbon-emissions/carbon-emissions-11.png" width="90%" /> --- class: inverse <img src="data:image/png;base64,#img/carbon-emissions/carbon-emissions-12.png" width="80%" /> --- class: inverse <img src="data:image/png;base64,#img/carbon-emissions/carbon-emissions-13.png" width="80%" /> --- .center[ .large[ Now, your turn! Open the **exercise-01 carbon emissions** project in RStudio Cloud! ] ] <img src="data:image/png;base64,#img/carbon-emissions/carbon-emissions-14.png" width="60%" /> --- .center[ .large[ This class content was built from the Data Science in a Box source materials. https://datasciencebox.org/index.html ] ]